Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Market-Based Explanations of Collective Decisions
Authors: Dominik Peters, Grzegorz Pierczyński, Nisarg Shah, Piotr Skowron5656-5663
AAAI 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We show that, unfortunately, SP committees do not always exist. However, through a series of extensive experiments, we argue that almost SP committees often do (specifically ones whose size is very close to k); see Appendix D for details. Finally, we adapt the notion of Lindahl equilibrium to the committee election context, and show that SP is closely related to it. |
| Researcher Affiliation | Academia | Dominik Peters, 1 Grzegorz Pierczy nski, 2 Nisarg Shah, 3 Piotr Skowron 2 1Harvard University 2University of Warsaw 3University of Toronto |
| Pseudocode | No | The paper describes concepts and algorithms but does not provide pseudocode or a clearly labeled algorithm block. |
| Open Source Code | No | The paper does not provide any statement or link indicating the release of source code for the described methodology. |
| Open Datasets | No | The paper mentions using 'real datasets' but does not provide specific access information (link, DOI, repository, or a formal citation for the dataset itself) for them. |
| Dataset Splits | No | The paper does not provide specific details regarding training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory amounts) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library names with version numbers, needed to replicate the experiment. |
| Experiment Setup | No | The paper does not provide specific experimental setup details like hyperparameter values or training configurations. |